Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 977 680 619 890 411 472 621 634 833 537 600 298 639 737 500 344 686 15 273 719
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 537 298 619 977 344 621 411 600 472 833 686 737 634 NA 719 NA 680 273 500 15 639 NA 890
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 1 1 5 3 3 4 5 1 1 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "o" "b" "q" "y" "s" "U" "H" "X" "N" "F"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 1
which( manyNumbersWithNA > 900 )
[1] 4
which( is.na( manyNumbersWithNA ) )
[1] 14 16 22
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 977
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 977
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 977
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "U" "H" "X" "N" "F"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "o" "b" "q" "y" "s"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 5 6 10 11 15 16
sum( manyNumbers %in% 300:600 )
[1] 6
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "small" "large" "large" "small" "large" "small" "large" "small" "large" "large" "large" "large" NA "large" NA "large" "small" "large" "small" "large" NA
[23] "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "small" "large" "large" "small" "large" "small" "large" "small" "large" "large" "large" "large" "UNKNOWN" "large" "UNKNOWN" "large" "small"
[19] "large" "small" "large" "UNKNOWN" "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 537 0 619 977 0 621 0 600 0 833 686 737 634 NA 719 NA 680 0 500 0 639 NA 890
unique( duplicatedNumbers )
[1] 1 5 3 4
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 1 5 3 4
duplicated( duplicatedNumbers )
[1] FALSE TRUE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 4
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 977
which.min( manyNumbersWithNA )
[1] 20
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 15
range( manyNumbersWithNA, na.rm = TRUE )
[1] 15 977
manyNumbersWithNA
[1] 537 298 619 977 344 621 411 600 472 833 686 737 634 NA 719 NA 680 273 500 15 639 NA 890
sort( manyNumbersWithNA )
[1] 15 273 298 344 411 472 500 537 600 619 621 634 639 680 686 719 737 833 890 977
sort( manyNumbersWithNA, na.last = TRUE )
[1] 15 273 298 344 411 472 500 537 600 619 621 634 639 680 686 719 737 833 890 977 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 977 890 833 737 719 686 680 639 634 621 619 600 537 500 472 411 344 298 273 15 NA NA NA
manyNumbersWithNA[1:5]
[1] 537 298 619 977 344
order( manyNumbersWithNA[1:5] )
[1] 2 5 1 3 4
rank( manyNumbersWithNA[1:5] )
[1] 3 1 4 5 2
sort( mixedLetters )
[1] "b" "F" "H" "N" "o" "q" "s" "U" "X" "y"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 7.5 9.5 2.5 5.0 6.0 7.5 2.5 2.5 2.5 9.5
rank( manyDuplicates, ties.method = "min" )
[1] 7 9 1 5 6 7 1 1 1 9
rank( manyDuplicates, ties.method = "random" )
[1] 7 10 1 5 6 8 2 4 3 9
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 0.40792859 0.91978336 1.48008294 -1.12321738 -0.09543070 -0.15947533 -2.02231691 0.01152684 0.41247024 1.23684199
round( v, 0 )
[1] -1 0 0 0 1 0 1 1 -1 0 0 -2 0 0 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.4 0.9 1.5 -1.1 -0.1 -0.2 -2.0 0.0 0.4 1.2
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.41 0.92 1.48 -1.12 -0.10 -0.16 -2.02 0.01 0.41 1.24
floor( v )
[1] -1 -1 0 0 1 0 0 1 -2 -1 -1 -3 0 0 1
ceiling( v )
[1] -1 0 0 1 1 1 1 2 -1 0 0 -2 1 1 2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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